Algolia Data Modeling

Use this skill to shape the data before code writes records to Algolia. Good relevance usually starts with records that match the user journey, not the source database schema.

Customer-Facing Standard

• Ask for sample records and edge cases before making record-shape claims.
• State assumptions plainly when source data is missing.
• Use public academy.algolia.com for learning alignment and public algolia.com/doc for current implementation guidance when source-backed context is needed.
• When an Academy metadata reference pack is available, use only its title, url, course, module, learning_objectives, and updated_at fields for structure. If it is stale or no match exists, fall back to live Academy/docs lookup. Do not treat cached metadata as course content or implementation authority.
• Do not require custom Academy/docs access; use customer-provided sources only as optional context.
• When live Algolia data, analytics, index inspection, settings changes, or account actions are needed, use Algolia MCP, the Algolia CLI, or official Algolia skills for the live operation, then apply this skill to interpret results and validate the customer-ready implementation path.
• Produce an indexing contract, validation queries, owner handoff, and reindex/update path.
• For ecommerce catalogs, explicitly choose between variant-level, variation-group-level, and product-level record models before discussing merchandising or UI behavior.

Official Companion Skills

• Use official algolia-mcp or algolia-cli when live sample records, existing index shape, object counts, imports, or exports need to be inspected.
• Use this skill after the official tool call to turn findings into a customer-facing indexing contract, variant strategy, and validation plan.